Marker-assisted selection in sheep and goats

Sheep and goats are often kept in low input production systems, often at subsistence levels. In such systems, the uptake of effective commercial breeding programmes is limited, let alone the uptake of more advanced technologies such as those needed for marker-assisted selection (MAS). However, effective breeding programmes exist in a number of countries, the largest ones in Australia and New Zealand aiming for genetic improvement of meat and wool characteristics as well as disease resistance and fecundity. Advances have been made in sheep gene mapping with the marker map consisting of more than 1 200 microsatellites, and a virtual genome sequence together with a very dense single nucleotide polymorphism (SNP) map are expected within a year. Significant research efforts into quantitative trait loci (QTL) are under way and a number of commercial sheep gene tests have already become available, mainly for single gene effects but some for muscularity and disease resistance. Gene mapping in goats is much less advanced with mainly some activity in dairy goats. Integration of genotypic information into commercial genetic evaluation and optimal selection strategies is a challenge that deserves more development

Optimal development of the Australian sheep genetic resources

The Australian sheep industry is at a crossroads where technical opportunities allow rapid genetic change, and market developments tend to favour a shift in profitability from wool to meat production. A key question is how the existing genetic resources should be developed optimally to maximize future profitability across the Australian sheep industry. Breeding objectives need to be developed jointly for wool and terminal sire breeds, taking into account the joint use of these breeds in a crossbreeding system. A simple model was trialed, optimizing profit per unit of feed, suggesting that a crossbreeding system remains in place with specialized wool and meat breeds. Optimal development involves increased body size for meat breeds but increased wool production and quality and decreased body size for wool breeds that also serve as dams of prime lambs. Both wool and meat breeds should increase reproductive rate

Is it useful to define residual feed intake as a trait in animal breeding programs?

Residual feed intake is a linear function of feed intake, production and maintenance of liveweight, and as such is an attractive characteristic to use to represent production efficiency. The phenotypic and genetic parameters of residual feed intake can be written as a function of its constituent traits. Moreover, selection indices containing the constituent traits are equivalent with an index that includes residual feed intake. Therefore, definition of the term residual feed intake may be useful to interpret variation in production efficiency, but it does not help in obtaining a better selection response than selection on constituent traits alone. In fact, multiple trait genetic evaluation of constituent traits rather than residual feed intake is likely to be more accurate as this more appropriately accommodates different models for the constituent traits and missing data. For residual feed intake to reflect true biological efficiency in growing animals, it is important that feed intake and liveweight are accurately measured. Accounting for growth and body composition would significantly help in revealing between-animal variation in feed utilisation. Random regression models can be helpful in indicating variation in feed efficiency over the growth trajectory

Optimising selection on growth and carcase development trajectories in lamb

Net benefit of response to selection for weight, fat and eye muscle depth measured at different ages was optimized for lamb production systems. Optimised selection response and profit were compared for an index based on random regression coefficients relating to the whole growth trajectory and an index based on breeding value for weight, fat and muscle at 200 days. Three different price structures were considered with various premiums for fat and muscle. No significant additional benefit was gained from using random regression breeding value over selection for traits at 200 days of age for a terminal sire breeding objective. However more additional benefit might be expected for a case where maternal performance is considered in the objective or when feed costs are high

Efficient designs for fine-mapping of quantitative trait loci using linkage disequilibrium and linkage

This study showed that common half sib designs can obtain sufficient linkage disequilibrium (LD) information for fine-mapping of quantitative trait loci (QTL). A design of two large half sib families was applied to a hypothetical population with an effective size (Ne) of 1000 simulated for 6000 generations. 70 ~ 75% of replicates could position QTL within 0.75 cM when mutation age was more than 200 generations in mapping using multi-allelic markers. When Ne was linearly decreasing (1000 to 100) in the last 50 generations, the accuracy of QTL mapping was decreased to only 50 to 70% of replicates that could position QTL within 0.75 cM. Provided that QTL allele segregates in the dam population, it is advantageous to use the same half sib design in linkage mapping and fine-mapping making gene mapping cost effective in livestock populations

Fine mapping of multiple interacting quantitative trait loci using combined linkage disequilibrium and linkage information

Quantitative trait loci (QTL) and their additive, dominance and epistatic effects play a critical role in complex trait variation. It is often infeasible to detect multiple interacting QTL due to main effects often being confounded by interaction effects. Positioning interacting QTL within a small region is even more difficult. We present a variance component approach nested in an empirical Bayesian method, which simultaneously takes into account additive, dominance and epistatic effects due to multiple interacting QTL. The covariance structure used in the variance component approach is based on combined linkage disequilibrium and linkage (LDL) information. In a simulation study where there are complex epistatic interactions between QTL, it is possible to simultaneously fine map interacting QTL using the proposed approach. The present method combined with LDL information can efficiently detect QTL and their dominance and epistatic effects, making it possible to simultaneously fine map main and epistatic QTL

An efficient variance component approach implementing an average information REML suitable for combined LD and linkage mapping with a general complex pedigree

Variance component (VC) approaches based on restricted maximum likelihood (REML) have been used as an attractive method for positioning of quantitative trait loci (QTL). Linkage disequilibrium (LD) information can be easily implemented in the covariance structure among QTL effects (e.g. genotype relationship matrix) and mapping resolution appears to be high. Because of the use of LD information, the covariance structure becomes much richer and denser compared to the use of linkage information alone. This makes an average information (AI) REML algorithm based on mixed model equations and sparse matrix techniques less useful. In addition, (near-) singularity problems often occur with high marker densities, which is common in fine-mapping, causing numerical problems in AIREML based on mixed model equations. The present study investigates the direct use of the variance covariance matrix of all observations in AIREML for LD mapping with a general complex pedigree. The method presented is more efficient than the usual approach based on mixed model equations and robust to numerical problems caused by near-singularity due to closely linked markers. It is also feasible to fit multiple QTL simultaneously in the proposed method whereas this would drastically increase computing time when using mixed model equation-based methods

Fine-mapping of quantitative trait loci using combined linkage disequilibrium and linkage with general pedigrees

Linkage disequilibrium (LD) information from closely linked markers has been widely used to fine-map quantitative trait loci (QTL). Steps needed for fine-mapping of QTL include inferring inheritance state of markers (haplotyping), estimating identity by descent (IBD) at QTL, and implementing the covariance structure based on IBD into a statistical model. Appropriate pedigree-genotype analysis can estimate more accurate inheritance state and haplotype configuration, which results in more accurate IBD probabilities. A variance component approach can implement covariance coefficients based on IBD probabilities in a mixed linear model to fit additive, dominance and epistasis QTL effects. We have also implemented a reversible jump Markov chain Monte Carlo (MCMC) method for multiple QTL mapping to account for confounding effects between closely linked QTL. Simulation results have shown that this method can improve the precision of mapping QTL

Fine mapping of multiple QTL using a reversible jump MCMC

There may be multiple QTL underlying phenotypes of a trait within a small region. The effects of closely linked QTL can be easily confounded which may negatively affect precision and accuracy of mapping of each QTL. Multiple QTL in such a small region may be considered as a single QTL, therefore the confidence interval covers all of the region. This makes fine mapping of each QTL impossible. The question is how easy multiple QTL within a small region can be accurately mapped. In this paper, we propose the use of a reversible jump MCMC (Green, 1995) in a variance component approach using combined LD and linkage (LDL) information to simultaneously map multiple QTL in a small region. The use of population wide LD can give critical information about different identity by descent (IBD) probabilities in different chromosome segments. The aim of this study is to investigate the efficiency of simultaneous mapping of multiple closely linked QTL with a proper model selection approach such as a reversible jump MCMC

Using dominance relationship coefficients based on linkage disequilibrium and linkage with a general complex pedigree to increase mapping resolution

Dominance (intra-locus allelic interactions) plays often an important role in quantitative trait variation. However, few studies about dominance in QTL mapping have been reported in outbred animal or human populations. This is because common dominance effects can be predicted mainly for many full sibs which are not often occurring in outbred or natural populations with a general pedigree. Moreover, incomplete genotypes for such a pedigree make it infeasible to estimate dominance relationship coefficients between individuals. In this study, identity by descent (IBD) coefficients are estimated based on population wide linkage disequilibrium (LD), which makes it possible to tract dominance relationships between unrelated founders. Therefore, it is possible to use dominance effects in QTL mapping without full sibs. Incomplete genotypes with complex pedigree and many markers can be efficiently dealt with a Markov chain Monte Carlo method for estimating IBD and dominance relationship matrices (DRM). It is shown by simulation that the use of DRM increases the likelihood ratio at the true QTL position, and the mapping accuracy and power with complete dominance, overdominance and recessive inheritance modes when using 200 genotyped and phenotyped individuals